Appl Opt. 2023 Apr 20;62(12):3062-3071. doi: 10.1364/AO.481140.
There has been much research on how to restore a single image from distorted video. Random water surface variation, an inability to model the surface, and multiple factors in the imaging processing leading to different geometric distortions in each frame are among the challenges. This paper proposes an inverted pyramid structure based on the cross optical flow registration approach and a multi-scale weight fusion method based on wavelet decomposition. The inverted pyramid based on the registration method is used to estimate the original pixel positions. A multi-scale image fusion method is applied to fuse the two inputs processed by optical flow and backward mapping, and two iterations are proposed to improve the accuracy and stability of the output video. The method is tested on several reference distorted videos and our videos, which were obtained through our experimental equipment. The obtained results exhibit significant improvements over other reference methods. The corrected videos obtained with our approach have a higher degree of sharpness, and the time required to restore the videos is significantly reduced.
已经有很多关于如何从失真视频中恢复单张图像的研究。随机水面变化、无法对表面建模以及成像处理中的多种因素导致每一帧中的几何变形不同，这些都是挑战。本文提出了一种基于交叉光流配准方法和基于小波分解的多尺度权重融合方法的倒金字塔结构。基于配准方法的倒金字塔用于估计原始像素位置。应用多尺度图像融合方法融合光流和反向映射处理的两个输入，并提出两个迭代步骤以提高输出视频的准确性和稳定性。该方法在几个参考失真视频和我们的实验设备获取的视频上进行了测试。得到的结果显示，与其他参考方法相比有显著的改进。使用我们的方法获得的校正视频具有更高的清晰度，并且恢复视频所需的时间大大减少。
